1. Research Methods

2. Descriptive Methods • Observation • Survey Research • Experimental Methods • Independent Groups Designs • Repeated Measures Designs • Complex Designs • Applied Research • Single-Case Designs and Small-n Research • Quasi-Experimental Designs and Program Evaluation

3. Experimental Methods • PSYCHOLOGICAL EXPERIMENTS • LOGIC OF EXPERIMENTAL RESEARCH • RANDOM GROUPS DESIGN • Block Randomization • Threats to Internal Validity • ANALYSIS AND INTERPRETATION OF EXPERIMENTAL FINDINGS • The Role of Data Analysis in Experiments • Describing the Results • Confirming What the Results Reveal • What Data Analysis Can’t Tell Us • ESTABLISHING THE EXTERNAL VALIDITY OF EXPERIMENTAL FINDINGS • MATCHED GROUPS DESIGN • NATURAL GROUPS DESIGN Independent Groups Designs

4. Psychological Experiments • Experiments: • Empirical testing of hypotheses • Testing contemporary theories • Identification of the causes of behavior • Testing intervention

5. Logic of Experiments • Manipulation • IV on DV to observe the effect on behavior • Experimental control • causal inference (IV caused the observed changes in the DV) • Control is an essential ingredient • gained through manipulation, holding conditions constant, and balancing • Causal Inferences (three conditions) • covariation, time-order relationship, and elimination of plausible alternative causes. • When confounding occurs, a plausible alternative explanation for the observed covariation exists, and therefore, the experiment lacks internal validity. Plausible alternative explanations are ruled out by holding conditions constant and balancing

6. Random Groups Design • Each group of subjects participates in only one condition of IV • Comparable groups • Manipulation: Random assignment of conditions • Holding Conditions Constant • Balancing or averaging subject characteristics (individual differences) • independent groups for the levels of the independent variable • Dittmar et al. (2006) • Barbie,Emme, neutral

7. Block Randomization

8. Threats to Internal Validity • Intact groups: • Potential confounding due to preexisting differences • Balancing Extraneous Variables • Experimenter, observer • Selective subject loss > Mechanical subject loss • Demand characteristics • Placebo control groups • Double-blind experiments

9. ANALYSIS AND INTERPRETATION OF EXPERIMENTAL FINDINGS • Good research question  Good experiment • Role of Data Analysis in Experiments • Statistics as Principled Argument (1995) by Robert Abelson • “primary goal of data analysis is to determine whether observations support a claim about behavior” • Replication  Reliability • Data analysis and statistics  Alternative to replication

10. Describing the Results • Descriptive statistics that • Mean (central tendency) • Standard deviation (variation/individual differences) • Measures of effect size • strength of the relationship and they are not affected by sample size. • Cohen’s’ d: More than mean difference • difference between two group means relative to the average variability • small, medium, and large effects (.20, .50, and .80) • Meta-analysis • Measures of effect size to summarize the results of many experiments investigating the same independent variable or dependent variable

11. Confirming What the Results Reveal • Inferential statistics • Reliable effect of IV on DV? • To infer results of sample on population • Difference due to chance (error variance) • Two methods (Null hypothesis testing and confidence intervals) • NHST • Probability theory whether difference is due to error variance • T-test, F-test etc. • A statistically significant = small likelihood of occurring if the null hypothesis < 5% • confidence intervals • Probability of CI (.95) • Width of interval (the narrower the better) • Degree of overlap  reliable difference of sample means

12. What Data Analysis Can’t Tell Us • Results of study have practical value or even if they are meaningful? • No certainty regarding conclusion • Errors: • A Type I error: is like a false alarm—saying that there is a fire when there is not • Type II error: we have insufficient evidence to reject the null hypothesis and it is, in fact, false

13. ESTABLISHING THE EXTERNAL VALIDITY • External validity • Application to other individuals, settings, and conditions • Theory-testing • Emphasis on internal validity over external validity • Field experiments  increase the external validity • Partial replication  external validity • Generalization of conceptual relationships

14. MATCHED GROUPS DESIGN • A matched groups design • Too few subjects available for random assignment to work effectively • Matching • Best on the dependent variable tasks • After matching task • Random assignment to the conditions

15. NATURAL GROUPS DESIGN • Individual differences variables (or subject variables) are selected rather than manipulated to form natural groups designs. • The natural groups design represents a type of correlational research in which researchers look for covariations between natural groups variables and dependent variables. • Causal inferences cannot be made regarding the effects of natural groups variables because plausible alternative explanations for group differences exist.